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class TMVA::DataSet: public TNamed


DataSet

Class that contains all the data information

Function Members (Methods)

public:

virtual	~DataSet()
void	TObject::AbstractMethod(const char* method) const
void	AddEvent(TMVA::Event*, TMVA::Types::ETreeType)
virtual void	TObject::AppendPad(Option_t* option = "")
virtual void	TObject::Browse(TBrowser* b)
static TClass*	Class()
virtual const char*	TObject::ClassName() const
virtual void	TNamed::Clear(Option_t* option = "")
void	ClearNClassEvents(Int_t type)
virtual TObject*	TNamed::Clone(const char* newname = "") const
virtual Int_t	TNamed::Compare(const TObject* obj) const
virtual void	TNamed::Copy(TObject& named) const
void	CreateSampling() const
TMVA::DataSet	DataSet()
TMVA::DataSet	DataSet(const TMVA::DataSetInfo&)
TMVA::DataSet	DataSet(const TMVA::DataSet&)
virtual void	TObject::Delete(Option_t* option = "")MENU
void	DeleteResults(const TString&, TMVA::Types::ETreeType type, TMVA::Types::EAnalysisType analysistype)
virtual Int_t	TObject::DistancetoPrimitive(Int_t px, Int_t py)
void	DivideTrainingSet(UInt_t blockNum)
virtual void	TObject::Draw(Option_t* option = "")
virtual void	TObject::DrawClass() constMENU
virtual TObject*	TObject::DrawClone(Option_t* option = "") constMENU
virtual void	TObject::Dump() constMENU
virtual void	TObject::Error(const char* method, const char* msgfmt) const
void	EventResult(Bool_t successful, Long64_t evtNumber = -1)
virtual void	TObject::Execute(const char* method, const char* params, Int_t* error = 0)
virtual void	TObject::Execute(TMethod* method, TObjArray* params, Int_t* error = 0)
virtual void	TObject::ExecuteEvent(Int_t event, Int_t px, Int_t py)
virtual void	TObject::Fatal(const char* method, const char* msgfmt) const
virtual void	TNamed::FillBuffer(char*& buffer)
virtual TObject*	TObject::FindObject(const char* name) const
virtual TObject*	TObject::FindObject(const TObject* obj) const
TMVA::Types::ETreeType	GetCurrentType() const
virtual Option_t*	TObject::GetDrawOption() const
static Long_t	TObject::GetDtorOnly()
const TMVA::Event*	GetEvent() const
const TMVA::Event*	GetEvent(Long64_t ievt) const
const TMVA::Event*	GetEvent(Long64_t ievt, TMVA::Types::ETreeType type) const
const vector<TMVA::Event*>&	GetEventCollection(TMVA::Types::ETreeType type = Types::kMaxTreeType) const
const TTree*	GetEventCollectionAsTree()
virtual const char*	TObject::GetIconName() const
virtual const char*	TNamed::GetName() const
Long64_t	GetNClassEvents(Int_t type, UInt_t classNumber)
Long64_t	GetNEvents(TMVA::Types::ETreeType type = Types::kMaxTreeType) const
Long64_t	GetNEvtBkgdTest()
Long64_t	GetNEvtBkgdTrain()
Long64_t	GetNEvtSigTest()
Long64_t	GetNEvtSigTrain()
UInt_t	GetNSpectators() const
UInt_t	GetNTargets() const
Long64_t	GetNTestEvents() const
Long64_t	GetNTrainingEvents() const
UInt_t	GetNVariables() const
virtual char*	TObject::GetObjectInfo(Int_t px, Int_t py) const
static Bool_t	TObject::GetObjectStat()
virtual Option_t*	TObject::GetOption() const
TMVA::Results*	GetResults(const TString&, TMVA::Types::ETreeType type, TMVA::Types::EAnalysisType analysistype)
const TMVA::Event*	GetTestEvent(Long64_t ievt) const
virtual const char*	TNamed::GetTitle() const
const TMVA::Event*	GetTrainingEvent(Long64_t ievt) const
TTree*	GetTree(TMVA::Types::ETreeType type)
virtual UInt_t	TObject::GetUniqueID() const
virtual Bool_t	TObject::HandleTimer(TTimer* timer)
virtual ULong_t	TNamed::Hash() const
Bool_t	HasNegativeEventWeights() const
void	IncrementNClassEvents(Int_t type, UInt_t classNumber)
virtual void	TObject::Info(const char* method, const char* msgfmt) const
virtual Bool_t	TObject::InheritsFrom(const char* classname) const
virtual Bool_t	TObject::InheritsFrom(const TClass* cl) const
void	InitSampling(Float_t fraction, Float_t weight, UInt_t seed = 0)
virtual void	TObject::Inspect() constMENU
void	TObject::InvertBit(UInt_t f)
virtual TClass*	IsA() const
virtual Bool_t	TObject::IsEqual(const TObject* obj) const
virtual Bool_t	TObject::IsFolder() const
Bool_t	TObject::IsOnHeap() const
virtual Bool_t	TNamed::IsSortable() const
Bool_t	TObject::IsZombie() const
virtual void	TNamed::ls(Option_t* option = "") const
void	TObject::MayNotUse(const char* method) const
void	MoveTrainingBlock(Int_t blockInd, TMVA::Types::ETreeType dest, Bool_t applyChanges = kTRUE)
virtual Bool_t	TObject::Notify()
void	TObject::Obsolete(const char* method, const char* asOfVers, const char* removedFromVers) const
void	TObject::operator delete(void* ptr)
void	TObject::operator delete(void* ptr, void* vp)
void	TObject::operator delete[](void* ptr)
void	TObject::operator delete[](void* ptr, void* vp)
void*	TObject::operator new(size_t sz)
void*	TObject::operator new(size_t sz, void* vp)
void*	TObject::operator new[](size_t sz)
void*	TObject::operator new[](size_t sz, void* vp)
TMVA::DataSet&	operator=(const TMVA::DataSet&)
virtual void	TObject::Paint(Option_t* option = "")
virtual void	TObject::Pop()
virtual void	TNamed::Print(Option_t* option = "") const
virtual Int_t	TObject::Read(const char* name)
virtual void	TObject::RecursiveRemove(TObject* obj)
void	TObject::ResetBit(UInt_t f)
virtual void	TObject::SaveAs(const char* filename = "", Option_t* option = "") constMENU
virtual void	TObject::SavePrimitive(ostream& out, Option_t* option = "")
void	TObject::SetBit(UInt_t f)
void	TObject::SetBit(UInt_t f, Bool_t set)
void	SetCurrentEvent(Long64_t ievt) const
void	SetCurrentType(TMVA::Types::ETreeType type) const
virtual void	TObject::SetDrawOption(Option_t* option = "")MENU
static void	TObject::SetDtorOnly(void* obj)
void	SetEventCollection(vector<TMVA::Event>, TMVA::Types::ETreeType, Bool_t deleteEvents = true)
virtual void	TNamed::SetName(const char* name)MENU
virtual void	TNamed::SetNameTitle(const char* name, const char* title)
static void	TObject::SetObjectStat(Bool_t stat)
virtual void	TNamed::SetTitle(const char* title = "")MENU
virtual void	TObject::SetUniqueID(UInt_t uid)
void	SetVerbose(Bool_t)
virtual void	ShowMembers(TMemberInspector& insp) const
virtual Int_t	TNamed::Sizeof() const
virtual void	Streamer(TBuffer&)
void	StreamerNVirtual(TBuffer& ClassDef_StreamerNVirtual_b)
virtual void	TObject::SysError(const char* method, const char* msgfmt) const
Bool_t	TObject::TestBit(UInt_t f) const
Int_t	TObject::TestBits(UInt_t f) const
UInt_t	TreeIndex(TMVA::Types::ETreeType type) const
virtual void	TObject::UseCurrentStyle()
virtual void	TObject::Warning(const char* method, const char* msgfmt) const
virtual Int_t	TObject::Write(const char* name = 0, Int_t option = 0, Int_t bufsize = 0)
virtual Int_t	TObject::Write(const char* name = 0, Int_t option = 0, Int_t bufsize = 0) const

protected:

virtual void	TObject::DoError(int level, const char* location, const char* fmt, va_list va) const
void	TObject::MakeZombie()

private:

void	ApplyTrainingBlockDivision()
void	ApplyTrainingSetDivision()
void	DestroyCollection(TMVA::Types::ETreeType type, Bool_t deleteEvents)
TMVA::MsgLogger&	Log() const

Data Members

public:

static TObject::(anonymous)	TObject::kBitMask
static TObject::EStatusBits	TObject::kCanDelete
static TObject::EStatusBits	TObject::kCannotPick
static TObject::EStatusBits	TObject::kHasUUID
static TObject::EStatusBits	TObject::kInvalidObject
static TObject::(anonymous)	TObject::kIsOnHeap
static TObject::EStatusBits	TObject::kIsReferenced
static TObject::EStatusBits	TObject::kMustCleanup
static TObject::EStatusBits	TObject::kNoContextMenu
static TObject::(anonymous)	TObject::kNotDeleted
static TObject::EStatusBits	TObject::kObjInCanvas
static TObject::(anonymous)	TObject::kOverwrite
static TObject::(anonymous)	TObject::kSingleKey
static TObject::(anonymous)	TObject::kWriteDelete
static TObject::(anonymous)	TObject::kZombie

protected:

TString	TNamed::fName	object identifier
TString	TNamed::fTitle	object title

private:

vector<Char_t>	fBlockBelongToTraining	when dividing the dataset to blocks, sets whether
vector<vector<Long64_t> >	fClassEvents	number of events of class 0,1,2,... in training[0]
Long64_t	fCurrentEventIdx
UInt_t	fCurrentTreeIdx
vector<vector<TMVA::Event*> >	fEventCollection	list of events for training/testing/...
Bool_t	fHasNegativeEventWeights	true if at least one signal or bkg event has negative weight
TMVA::MsgLogger*	fLogger	! message logger
vector<map<TString,TMVA::Results*> >	fResults	! [train/test/...][method-identifier]
vector<Char_t>	fSampling	random or importance sampling (not all events are taken) !! Bool_t are stored ( no std::vector<bool> taken for speed (performance) issues )
vector<vector<pair<Float_t,Long64_t> > >	fSamplingEventList	weights and indices for sampling
vector<Int_t>	fSamplingNEvents	number of events which should be sampled
TRandom3*	fSamplingRandom	-> random generator for sampling
vector<vector<pair<Float_t,Long64_t> > >	fSamplingSelected	selected events
vector<Float_t>	fSamplingWeight	weight change factor [weight is indicating if sampling is random (1.0) or importance (<1.0)]
Long64_t	fTrainingBlockSize	block size into which the training dataset is divided
const TMVA::DataSetInfo*	fdsi	-> datasetinfo that created this dataset

Class Charts

Inheritance Chart:

TObject

←

TNamed

←

TMVA::DataSet

Function documentation

UInt_t TreeIndex(TMVA::Types::ETreeType type) const

TMVA::Types::ETreeType GetCurrentType() const

Long64_t GetNEvents(TMVA::Types::ETreeType type = Types::kMaxTreeType) const

const std::vector<TMVA::Event*>& GetEventCollection(TMVA::Types::ETreeType type = Types::kMaxTreeType) const

DataSet()

DataSet(const DataSetInfo&)

virtual ~DataSet()

void AddEvent(TMVA::Event* , TMVA::Types::ETreeType )

Long64_t GetNTrainingEvents() const

{ return GetNEvents(Types::kTraining); }

Long64_t GetNTestEvents() const

{ return GetNEvents(Types::kTesting); }

const Event* GetEvent() const

 const getters

const Event* GetEvent(Long64_t ievt) const

{ fCurrentEventIdx = ievt; return GetEvent(); }

const Event* GetTrainingEvent(Long64_t ievt) const

{ return GetEvent(ievt, Types::kTraining); }

const Event* GetTestEvent(Long64_t ievt) const

{ return GetEvent(ievt, Types::kTesting); }

const Event* GetEvent(Long64_t ievt, TMVA::Types::ETreeType type) const

UInt_t GetNVariables() const

UInt_t GetNTargets() const

UInt_t GetNSpectators() const

void SetCurrentEvent(Long64_t ievt) const

{ fCurrentEventIdx = ievt; }

void SetCurrentType(TMVA::Types::ETreeType type) const

{ fCurrentTreeIdx = TreeIndex(type); }

void SetEventCollection(vector<TMVA::Event*>* , TMVA::Types::ETreeType , Bool_t deleteEvents = true)

const TTree* GetEventCollectionAsTree()

Long64_t GetNEvtSigTest()

Long64_t GetNEvtBkgdTest()

Long64_t GetNEvtSigTrain()

Long64_t GetNEvtBkgdTrain()

Bool_t HasNegativeEventWeights() const

{ return fHasNegativeEventWeights; }

Results* GetResults(const TString& , TMVA::Types::ETreeType type, TMVA::Types::EAnalysisType analysistype)

void SetVerbose(Bool_t )

{}

void DivideTrainingSet(UInt_t blockNum)

 sets the number of blocks to which the training set is divided,
 some of which are given to the Validation sample. As default they belong all to Training set.

void MoveTrainingBlock(Int_t blockInd, TMVA::Types::ETreeType dest, Bool_t applyChanges = kTRUE)

 sets a certrain block from the origin training set to belong to either Training or Validation set

void IncrementNClassEvents(Int_t type, UInt_t classNumber)

Long64_t GetNClassEvents(Int_t type, UInt_t classNumber)

void ClearNClassEvents(Int_t type)

TTree* GetTree(TMVA::Types::ETreeType type)

void InitSampling(Float_t fraction, Float_t weight, UInt_t seed = 0)

 accessors for random and importance sampling

void EventResult(Bool_t successful, Long64_t evtNumber = -1)

void CreateSampling() const

void DestroyCollection(TMVA::Types::ETreeType type, Bool_t deleteEvents)

 data members

void ApplyTrainingBlockDivision()

void ApplyTrainingSetDivision()